{"id":"https://openalex.org/W2962802054","doi":"https://doi.org/10.18653/v1/p18-2007","title":"Domain Adapted Word Embeddings for Improved Sentiment Classification","display_name":"Domain Adapted Word Embeddings for Improved Sentiment Classification","publication_year":2018,"publication_date":"2018-01-01","ids":{"openalex":"https://openalex.org/W2962802054","doi":"https://doi.org/10.18653/v1/p18-2007","mag":"2962802054"},"language":"en","primary_location":{"id":"doi:10.18653/v1/p18-2007","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p18-2007","pdf_url":"https://www.aclweb.org/anthology/P18-2007.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.aclweb.org/anthology/P18-2007.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5056582268","display_name":"Prathusha K Sarma","orcid":"https://orcid.org/0000-0002-1621-2011"},"institutions":[{"id":"https://openalex.org/I135310074","display_name":"University of Wisconsin\u2013Madison","ror":"https://ror.org/01y2jtd41","country_code":"US","type":"education","lineage":["https://openalex.org/I135310074"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Prathusha K Sarma","raw_affiliation_strings":["University of Wisconsin-Madison"],"affiliations":[{"raw_affiliation_string":"University of Wisconsin-Madison","institution_ids":["https://openalex.org/I135310074"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035905957","display_name":"Yingyu Liang","orcid":"https://orcid.org/0000-0002-3644-774X"},"institutions":[{"id":"https://openalex.org/I135310074","display_name":"University of Wisconsin\u2013Madison","ror":"https://ror.org/01y2jtd41","country_code":"US","type":"education","lineage":["https://openalex.org/I135310074"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yingyu Liang","raw_affiliation_strings":["University of Wisconsin-Madison"],"affiliations":[{"raw_affiliation_string":"University of Wisconsin-Madison","institution_ids":["https://openalex.org/I135310074"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5033605232","display_name":"Bill Sethares","orcid":null},"institutions":[{"id":"https://openalex.org/I135310074","display_name":"University of Wisconsin\u2013Madison","ror":"https://ror.org/01y2jtd41","country_code":"US","type":"education","lineage":["https://openalex.org/I135310074"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Bill Sethares","raw_affiliation_strings":["University of Wisconsin-Madison"],"affiliations":[{"raw_affiliation_string":"University of Wisconsin-Madison","institution_ids":["https://openalex.org/I135310074"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5056582268"],"corresponding_institution_ids":["https://openalex.org/I135310074"],"apc_list":null,"apc_paid":null,"fwci":5.3749,"has_fulltext":true,"cited_by_count":40,"citation_normalized_percentile":{"value":0.96568929,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9983000159263611,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.7820614576339722},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7780228853225708},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.6991462707519531},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.6791359186172485},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6398648619651794},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.5821681618690491},{"id":"https://openalex.org/keywords/canonical-correlation","display_name":"Canonical correlation","score":0.5695003271102905},{"id":"https://openalex.org/keywords/sentiment-analysis","display_name":"Sentiment analysis","score":0.5429290533065796},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.5052047371864319},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.4881077706813812},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3514082431793213},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1746867299079895}],"concepts":[{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.7820614576339722},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7780228853225708},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.6991462707519531},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.6791359186172485},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6398648619651794},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5821681618690491},{"id":"https://openalex.org/C153874254","wikidata":"https://www.wikidata.org/wiki/Q115542","display_name":"Canonical correlation","level":2,"score":0.5695003271102905},{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.5429290533065796},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.5052047371864319},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.4881077706813812},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3514082431793213},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1746867299079895},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/p18-2007","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p18-2007","pdf_url":"https://www.aclweb.org/anthology/P18-2007.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/p18-2007","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p18-2007","pdf_url":"https://www.aclweb.org/anthology/P18-2007.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.49000000953674316}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2962802054.pdf","grobid_xml":"https://content.openalex.org/works/W2962802054.grobid-xml"},"referenced_works_count":32,"referenced_works":["https://openalex.org/W342285082","https://openalex.org/W1167997707","https://openalex.org/W1486649854","https://openalex.org/W1771428564","https://openalex.org/W1828724394","https://openalex.org/W1933349210","https://openalex.org/W2025341678","https://openalex.org/W2051004098","https://openalex.org/W2062118960","https://openalex.org/W2067624665","https://openalex.org/W2100235303","https://openalex.org/W2115124945","https://openalex.org/W2145287260","https://openalex.org/W2153579005","https://openalex.org/W2163302275","https://openalex.org/W2250539671","https://openalex.org/W2251939518","https://openalex.org/W2293958442","https://openalex.org/W2295584157","https://openalex.org/W2296724235","https://openalex.org/W2302333170","https://openalex.org/W2461871142","https://openalex.org/W2514776376","https://openalex.org/W2609940642","https://openalex.org/W2739480064","https://openalex.org/W2950171587","https://openalex.org/W2963488396","https://openalex.org/W2963804993","https://openalex.org/W2963918774","https://openalex.org/W4237723258","https://openalex.org/W4294170691","https://openalex.org/W4297798444"],"related_works":["https://openalex.org/W4200241356","https://openalex.org/W4307004515","https://openalex.org/W2894707301","https://openalex.org/W2353067490","https://openalex.org/W2338093180","https://openalex.org/W2799129705","https://openalex.org/W868942698","https://openalex.org/W2952686743","https://openalex.org/W4292346614","https://openalex.org/W2798838888"],"abstract_inverted_index":{"Generic":[0],"word":[1,12,50,57],"embeddings":[2,13,35,80,87],"are":[3,14,52],"trained":[4,15],"on":[5,17,72],"large-scale":[6],"generic":[7,34,84],"corpora;":[8],"Domain":[9,47],"Specific":[10],"(DS)":[11],"only":[16],"data":[18],"from":[19],"a":[20,27],"domain":[21,40],"of":[22,33,39],"interest.":[23],"This":[24],"paper":[25],"proposes":[26],"method":[28],"to":[29,93],"combine":[30],"the":[31,37,65,78],"breadth":[32],"with":[36],"specificity":[38],"specific":[41],"embeddings.":[42],"The":[43],"resulting":[44],"embeddings,":[45,51],"called":[46],"Adapted":[48],"(DA)":[49],"formed":[53],"by":[54],"aligning":[55],"corresponding":[56],"vectors":[58],"using":[59],"Canonical":[60],"Correlation":[61],"Analysis":[62],"(CCA)":[63],"or":[64,95],"related":[66],"nonlinear":[67],"Kernel":[68],"CCA.":[69],"Evaluation":[70],"results":[71],"sentiment":[73],"classification":[74],"tasks":[75],"show":[76],"that":[77],"DA":[79],"substantially":[81],"outperform":[82],"both":[83],"and":[85],"DS":[86],"when":[88],"used":[89],"as":[90],"input":[91],"features":[92],"standard":[94],"state-of-the-art":[96],"sentence":[97],"encoding":[98],"algorithms":[99],"for":[100],"classification.":[101]},"counts_by_year":[{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":9},{"year":2020,"cited_by_count":13},{"year":2019,"cited_by_count":11}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}